Magnetic resonance (MR) is a widely practiced and growing alternative treatment for many indications (i.e., illness, disease, medical condition, or ailment). Magnetic resonance devices have been known to be a natural and economical means of treating body pains and common injuries. Many methods have been used to apply magnets to comfort or heal body areas and thereby, avoiding the use of injections, pills, salves, or body-invasive procedures. Overall, the basis of magnetic resonance involves artificially produced fields. These fields interact with components such as, but not limited to, atomic or molecular components of living tissue, which then have a beneficial effect on that living tissue.
One form of magnetic resonance uses static magnetic fields. Static magnetic fields may be produced by permanent magnets incorporated into items such as bracelets, belts, back pads, mattress pads, and mattresses. It is believed that static magnetic fields have some efficacy in the treatment of broken bones and soft tissue injuries and tend to promote the circulation of blood as well as relieve stiffness in muscles.
More recent attempts to employ the therapeutic effects of magnetic fields have focused on devices that generate an electromagnetic field and the methods of treatment employing such devices in conjunction with computers. Various devices have been made to create time-varying magnetic fields for use on the human body. Specifically, in this time-varying magnetic field device are pulsed electromagnetic fields (PEMFs) which are generated when a current is forced to move through a conductor in discrete impulses of electric charge moving in the same direction. These devices have been used to treat pain and relieve symptoms, as disclosed, for example, in Jacobson, et al., in U.S. Pat. No. 5,269,746.
The ability of PEMFs to affect changes in the body is dependant on the ability of PEMFs to positively affect human physiologic or anatomic systems. The pulsed magnetic waves use low power electromagnetic fields that stimulate the cells in the body to trigger healing. One implementation of PEMFs involves selecting field strengths and frequencies that resonate with the cellular frequencies in the body. Recent research has found improved efficacy when very low PEMFs are tuned precisely to the indication or condition of the subject. Thus, there exists a need to enable this type of PEMF delivery to subjects.
Currently, medical practitioners and medical researchers worldwide, generalists or specialists, treat a broad range of diseases through the use of conventional medicine. With the use of magnetic resonance devices and treatment protocols, these practitioners and researchers have the potential to treat subjects who suffer from a wide range of diseases in a more efficient and minimally invasive manner. Present magnetic resonance device systems, however, require the expertise of a magnetic therapist who understands magnetic resonance, as well as subject treatments and diseases in order to treat a subject. Additionally, in research settings, current magnetic resonance devices are only used by magnetic resonance experts to develop new magnetic resonance protocols. Consequently, only magnetic resonance experts can administer the treatment, limiting its use while the public suffers from a shortage of magnetic resonance treatment professionals.
By creating a simplified magnetic resonance device system that allows a broader range of users such as, but not limited to, medical practitioners, alternative medicine providers, or home users, more patients suffering from a wide range diseases may be treated by either treating themselves or with the assistance of a general practitioner. Additionally, such a device can be used by non-medical personnel in connection with other uses, such as relaxation. Medical researchers who do not have a special expertise in magnetic resonance may contribute to the development of new and improved magnetic resonance treatment parameters and protocols for a broad range of diseases. Additionally, users such as patients can operate and treat themselves using the magnetic resonance device remotely, such as at home, eliminating the need to travel to or make appointments with a medical practitioner. Accordingly, there exists a need for a system that does not require an expertise in magnetic resonance such that more health-care practitioners, researchers, and subjects are able to use magnetic resonance devices and treatment protocols. Thus, there exists a need for a simplified magnetic resonance device system that allows a broad range of users to administer magnetic resonance treatments and to contribute to the development of new and improved magnetic resonance parameters and protocols.
Furthermore, current systems do not aggregate, analyze, and improve subject magnetic resonance development data and thus, do not provide the most current treatment protocols available. These systems do not provide therapies for subjects suffering across multiple disease states and/or conditions (“co-morbidities”) in addition to their primary disease. Although there are a broad range of applications for treatment with PEMFs, the results of magnetic resonance treatment depend not only on the parameters of the fields, but also on the individual sensitivity of the person. A subject's predominant indication, medical history, biographical history, and prior treatment data, influence the subject's treatment parameters. Without using a subject's current state of health, prior medical history, and therapies that cover multiple disease states and/or conditions, current systems merely provide efficacious results to small homogenous populations found in clinical trials, rather than effective results across the diverse populations found in the real world, leaving the real subjects without the intended result.
Moreover, current systems lack the ability to capture and immediately consider the subject's sensitivity or biometric data through real-time data monitoring, increasing the risk of treatment error. An individual subject is generally required to heavily rely on the physician to set-up, administer, and adjust their treatment parameters without the benefit of receiving real-time data measurements during their treatment session. These real-time measurements can provide a compilation of data useful for analytical purposes in selecting future treatment protocols for subjects.
Additionally, if the system does not provide a systematic method of evaluating the subject's progress as the subject receives the treatment, the treatment parameters may not be readily adaptable. The treatment parameters may not be able to be modified at the subject's point of care if the operator does not have an expertise in magnetic resonance theory. In order to provide a method of evaluating a subject's progress as the subject receives a treatment, there exists a need for a system to capture and aggregate biometric measurement information for making real-time adjustments to current treatment parameters and a need to store information for analysis of future treatment protocols.
Also, currently a subject may provide verbal feedback of a treatment to his or her physician immediately after being given their magnetic resonance treatment. However, this may cause poor or incomplete information to be relayed to the physician when working with certain subject populations such as elderly subjects, children, patients suffering from dementia, or subjects within the general population who are inconvenienced (e.g., lack of time). In that case, the subject may not provide any feedback at all, or will provide a hastily given, and possibly less thorough, feedback response. Moreover, the feedback provided by the subject may typically be recorded in the subject's file by a physician and may not be in a format that lends itself to reporting. This creates a hindrance in quickly assessing the subject's treatment results and feedback data and stunts the research and development of better treatment protocols since non-identifiable subject data may be unable to be shared in a readily accessible and interactive medium.
In addition, current systems generally lack the ability to automatically understand a subject's progress through a systematic method of gathering feedback before, during, and after his treatment, regardless of the subject's location. Likewise, current systems lack the ability to for a subject to modify or to update his feedback responses after a treatment. The subject is expected to either make another appointment with the physician at a later date or wait until his next treatment in order to modify or update the feedback response to their prior treatment. This may cause the subject to fail to remember what modifications he wanted to make or to forget to address the modification at all. Consequently, a need exists for a flexible and accommodating method for the subject to provide and modify treatment feedback after his treatment and at his convenience. Thus, there exists a need for a readily accessible and interactive system to track and store reportable feedback given by subjects verbally, physically, biometrically, or by any other method of obtaining feedback, before, during, and after treatment.
Experts in the field of magnetic resonance continue to research the effect of PEMFs on various indications. For example, researchers test the effects of various PEMF parameters. As a result, researchers discover new and improved treatment parameters to apply in a clinical setting. One challenge is that these experts in the field of magnetic resonance may be isolated with their research and findings. It would be beneficial to compile and analyze this parameter data in order to use it to develop, improve, and define magnetic resonance treatment parameters. But current systems do not have this functionality, which negatively affects the ability of the physician to successfully treat or significantly benefit the myriad of symptoms presented to him with magnetic resonance treatment and the ability of the subject to receive new or improved treatment parameters.
Moreover, the current system lacks the ability to compile and measure actual subject results and feedback and provide improved treatment parameters based upon the compilation and analysis of those results and feedback. Each subject's results and feedback remain isolated. Thus, there exists a need for a system to compile, measure, and analyze subject results and feedback from magnetic resonance treatment and provide new or improved treatment parameters based upon the subject's results and feedback data. Additionally, there exists a need to integrate the system with web-based Health Insurance Portability and Accountability Act (“HIPAA”) compliant systems to gather results, feedback, and additional data from subjects, clinical or medical organizations, hospitals, or medical offices across a broad range of the subject population. Integrating these systems may allow information to be constantly updated, thereby creating more customized treatments and provide for new or improved treatment parameters.
Presently, magnetic resonance treatments are designed to treat or benefit symptoms associated with a specific indication. Existing treatment parameters typically treat only a specific symptom or indication, failing to take into account a subject's medical history. Current systems lack the ability to take into account a subject's medical history when setting magnetic resonance treatment parameters. A subject may have underlying conditions that need to be treated with magnetic resonance in addition to the subject's predominant indication. Furthermore, two subjects suffering from a common indication but with different medical histories are often treated with the same treatment parameters. This method of treatment ignores the different medical histories of each subject and does not reflect the reality of a living being.
Furthermore, current systems generally lack the ability to personalize treatment parameters to treat an individual subject. As a result, subjects may not receive the correct treatment parameters to directly treat their conditions. Moreover, a subject who is suffering from various indications may be required to receive multiple treatments to remedy his indications. For example, a subject may have a medical history that includes Parkinson's disease, as well as heart disease. A second subject may suffer only from heart disease. Using current systems, both subjects may receive similar treatment parameters to treat their heart disease. However, the first subject, who is suffering from multiple indications, may not receive the most appropriate treatment parameter to treat his multiple indications. This is inefficient, time-consuming, and may be mentally and physically exhausting for a subject suffering from multiple indications. Thus, there exists a need for a system to predict which treatments may be most useful in treating subjects with various subject histories, including subjects with multiple indications.
Additionally, current systems lack the ability to promptly access, analyze, and determine a subject's treatment regimen, past and current medical history, treatment results and feedback, and biographical data. The ability to perform these tasks would provide more efficient, reliable, and effective treatment, providing information for future treatment enhancements and reducing treatment errors. Presently, a physician is required to search through a subject's file for the subject's treatment regimen, past and current medical history, treatment results and feedback, and biographical data. Then, to provide magnetic resonance treatment to the subject, a physician must compute the magnetic resonance treatment parameters, or have such computation performed, which generally requires a specific level of expertise.
When determining the treatment parameters, however, a physician may lack the ability to consider all of the subject's parameters into his computation. Although a physician may consider the subject's indication and the subject's past treatment regimen, a physician may not have the ability, in the time allotted during the subject's magnetic resonance visit, to consider other variables that may have an impact on the computation of treatment parameters such the subject's past and current medical history, the medications the subject may be taking, the subject's physiological data (e.g., blood pressure, weight, tremor rate, or pulse rate), as well as the time, date, latitude and location of the subject's magnetic resonance treatments.
Although current systems may allow a physician to refine treatment parameters based upon the subject's verbal feedback and/or the physician's physical observation of the subject, the physician may lack the ability to calculate the subject's non-verbal, real-time data and feedback, such as physiological data, into the adjusted treatment parameters. As a result, the subject may not receive the most accurate treatment parameters. Thus, there exists a need for a system that incorporates multiple subject data and feedback parameters, as well as magnetic treatment data, into algorithms to compute the best magnetic resonance treatment parameters and protocols.